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Best α-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information
Methods that predict the topology of helical membrane proteins are standard tools when analyzing any proteome. Therefore, it is important to improve the performance of such methods. Here we introduce a novel method, PRODIV-TMHMM, which is a profile-based hidden Markov model (HMM) that also incorpora...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Cold Spring Harbor Laboratory Press
2004
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2279939/ https://ncbi.nlm.nih.gov/pubmed/15215532 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1110/ps.04625404 |
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